--- language: - pt task_categories: - token-classification pretty_name: Buscapé license: mit dataset_info: - config_name: default features: - name: tokens sequence: string - name: srl_frames list: - name: frames sequence: string - name: verb dtype: string splits: - name: train num_bytes: 215929 num_examples: 709 download_size: 47346 dataset_size: 215929 - config_name: flatten features: - name: tokens sequence: string - name: verb dtype: string - name: frames sequence: class_label: names: '0': B-A0 '1': B-A1 '2': B-A2 '3': B-A3 '4': B-A4 '5': B-AM-ADV '6': B-AM-ASP '7': B-AM-CAU '8': B-AM-COM '9': B-AM-DIS '10': B-AM-EXP '11': B-AM-EXT '12': B-AM-GOL '13': B-AM-LOC '14': B-AM-MNR '15': B-AM-MOD '16': B-AM-NEG '17': B-AM-NSE '18': B-AM-PAS '19': B-AM-PRD '20': B-AM-PRP '21': B-AM-TML '22': B-AM-TMP '23': B-C-A1 '24': B-C-A2 '25': B-C-AM-CAU '26': B-C-AM-MNR '27': B-C-AM-PRD '28': B-V '29': I-A0 '30': I-A1 '31': I-A2 '32': I-A3 '33': I-A4 '34': I-AM-ADV '35': I-AM-CAU '36': I-AM-COM '37': I-AM-EXT '38': I-AM-GOL '39': I-AM-LOC '40': I-AM-MNR '41': I-AM-NEG '42': I-AM-PRD '43': I-AM-PRP '44': I-AM-TMP '45': I-C-A1 '46': I-C-A2 '47': I-C-AM-CAU '48': O splits: - name: train num_bytes: 236352 num_examples: 709 download_size: 46914 dataset_size: 236352 configs: - config_name: default data_files: - split: train path: data/train-* - config_name: flatten data_files: - split: train path: flatten/train-* tags: - semantic role labelling - srl --- # Buscapé Sample annotated for Semantic Role Labelling ## Propbank-Br Corpora Buscapé Sample The Propbank-Br is a project that aims to annotate corpora with semantic role labels for the purpose of creating training datasets for automated semantic role classifiers. The annotation scheme is quite similar to that of the English Propbank (Palmer et al., 2005), with language-specific differences taken into account. The set of semantic roles was designed to facilitate automatic learning. The annotation is done on syntactic trees generated by the Palavras parser (Bick, 2000). This particular sample was annotated for the purpose of evaluating semantic role classifiers. It contains 840 instances annotated with semantic role labels on syntactic trees generated by the Palavras parser (Bick, 2000). The instances were extracted from the Buscapé corpus (Hartmann et al. 2014), a corpus of user reviews on products. The syntactic trees in the sample were not reviewed by humans, and were annotated using two annotators for each sentence (double-blind annotation). ## Data Treatment at LIAAD 131 propositions were excluded in this revision of the dataset. These included propositions with verb index annotation errors or no verb annotations, and propositions with more than one label for a word. Additionally, we removed arguments labeled as "AM-MED" or "AM-PIN" because there is no mention of these labels in the annotation guides, and we removed any propositions with flags "WRONGSUBCORPUS", "LATER" or "REEXAMINE", since, according to the guide, these indicate something wrong with the sentence that prevents its annotation. - **Annotated by:** [PROSA](https://sites.google.com/view/prosa-nilc) - **Language:** Portuguese ### Dataset Sources - **Link:** http://www.nilc.icmc.usp.br/semanticnlp/index.php?id=index&id_sub=principal&dir_sub=includes/projects/propbankbr&dir=includes/projects/propbankbr&lang=pt-br - **Paper:** Hartmann, N. S.; Avanço. L.; Balage, P. P.; Duran, M. S.; Nunes, M. G. V.; Pardo, T.; Aluísio, S. (2014). A Large Opinion Corpus in Portuguese - Tackling Out-Of-Vocabulary Words. In: Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC 2014). ## Citation **BibTeX:** ```bibtex @inproceedings{hartmann-etal-2014-large, title = "A Large Corpus of Product Reviews in {P}ortuguese: Tackling Out-Of-Vocabulary Words", author = "Hartmann, Nathan and Avan{\c{c}}o, Lucas and Balage, Pedro and Duran, Magali and das Gra{\c{c}}as Volpe Nunes, Maria and Pardo, Thiago and Alu{\'\i}sio, Sandra", editor = "Calzolari, Nicoletta and Choukri, Khalid and Declerck, Thierry and Loftsson, Hrafn and Maegaard, Bente and Mariani, Joseph and Moreno, Asuncion and Odijk, Jan and Piperidis, Stelios", booktitle = "Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)", month = may, year = "2014", address = "Reykjavik, Iceland", publisher = "European Language Resources Association (ELRA)", url = "http://www.lrec-conf.org/proceedings/lrec2014/pdf/413_Paper.pdf", pages = "3865--3871", abstract = "Web 2.0 has allowed a never imagined communication boom. With the widespread use of computational and mobile devices, anyone, in practically any language, may post comments in the web. As such, formal language is not necessarily used. In fact, in these communicative situations, language is marked by the absence of more complex syntactic structures and the presence of internet slang, with missing diacritics, repetitions of vowels, and the use of chat-speak style abbreviations, emoticons and colloquial expressions. Such language use poses severe new challenges for Natural Language Processing (NLP) tools and applications, which, so far, have focused on well-written texts. In this work, we report the construction of a large web corpus of product reviews in Brazilian Portuguese and the analysis of its lexical phenomena, which support the development of a lexical normalization tool for, in future work, subsidizing the use of standard NLP products for web opinion mining and summarization purposes.", } ``` **APA:** Hartmann, N. S., Avanço, L. V., Balage, P. P., Duran, M. S., Nunes, M. das G. V., Pardo, T. A. S., & Aluísio, S. M. (2014). A large corpus of product reviews in Portuguese: tackling out-of-vocabulary words. In Proceedings. Paris: ELRA. Recuperado de http://www.lrec-conf.org/proceedings/lrec2014/pdf/413_Paper.pdf ## Dataset Card Authors Rita Lopes | https://huggingface.co./rita443 | rita.n.lopes@inesctec.pt